The purpose of the Genetic/Genomic Data Analysis core is to provide the capacity to rigorously and[unreadable] efficiently address the overall hypothesis and goals of the proposed Center and its individual projects[unreadable] through state of the art approaches to quantitative genetics, genomics, health outcomes and integrated[unreadable] systems biology. The overall hypothesis of this application is that epithelial cell genes play a central role in[unreadable] the pathogenesis and successful treatment of allergic disorders; each of the projects has specific aims that[unreadable] address different aspects of this overall hypothesis. The aims of this Core are thus to: 1) provide study[unreadable] design, data management, and analysis support to the project investigators to fulfill their specific aims; 2)[unreadable] integrate data collected in the individual projects and thereby further interactions among projects on the role[unreadable] of epithelial genes in allergic inflammation; and 3) promote additional analyses and investigations that[unreadable] support the central theme and overall goals of this center. To fulfill these aims, this core includes an[unreadable] experienced set of faculty and staff with recognized expertise in statistical analysis, epidemiology,[unreadable] quantitative genetics, genomics, bioinformatics, and data management. Core investigators will meet routinely[unreadable] with each other, and with project investigators as needed. The PI of this core will meet routinely with project[unreadable] leadership to maintain accountability and prioritize the research support of the core. The primary projects[unreadable] described in this application involve analysis of samples and data derived from case-control and family[unreadable] studies that are based on large and growing registries of children seen at Cincinnati Children's with allergic[unreadable] disorders. These projects will require application of analytic methods appropriate for genetic epidemiology[unreadable] and microarray studies, including univariate comparisons and multivariable modelling to account for multiple[unreadable] genes and/or environmental factors as appropriate. The core will also support analysis of an extant[unreadable] population-based cohort of asthmatic children to test the replication of findings of the asthma case-control[unreadable] study conducted in project by Khurana.